There is a question I hear from technology leaders all the time. When is the right moment to begin with Industrial AI? Robi Gone gave me the clearest answer I have heard: the right moment is sooner than most people think, and the way to get there is to move deliberately, one proven step at a time. 

Robi is the Chief Information Officer at IFS, and he has spent 26 years leading transformation programmes inside large global enterprises, much of it in the energy and resources sector. So when he talks about how to build value from data, it carries the weight of someone who has delivered these programmes many times and knows exactly where the value sits. 

IFS Voices of Industry is a podcast that grounds the conversation around Industrial AI in real experience. Each episode brings together people across IFS who have spent time in the field, in hangars, on construction sites, and who now shape how AI is built and applied through IFS.ai. 

For Episode 7, I sat down with Robi to talk about what it takes to get an organisation ready for Industrial AI and how IFS guides customers through that journey. His perspective as a CIO gave the conversation a practical, architecture-level view that I think a lot of technology leaders will recognize. 

What needs to be true in your architecture to benefit from Industrial AI? 

Robi described the ideal foundation as clean, well-modelled, accessible data, or “drinkable data” as he memorably called it. Getting there is exactly the kind of work IFS is built to guide customers through, and it is why data sits at the heart of how IFS approaches AI. 

His most practical insight was about how to sequence that work. In every organisation, there are already areas where the data is strong enough to deliver value straight away. Robi’s advice is to begin in those areas, prove the value, and expand with confidence from a position of early success. 

“Be brave on your business case and then go.” 

I liked how directly he put that. For a CIO of his experience to say be brave is a sign of how much confidence he has in the maturity of the technology and in IFS’s ability to guide customers to a strong result. IFS brings the method and the rigour so that customers can move forward with certainty, building momentum as the underlying data estate strengthens alongside them. 

What is a match fit phase, and why does it de-risk transformation? 

A match fit phase is a preparation stage that happens before a transformation project formally begins. During it, teams examine the data, the integration points, the technical standards, and the deployment approach, so that the main programme starts from a well-prepared and de-risked position. 

Robi has used this approach on his last three major transformations, and each time the project landed on time, on scope, and to plan. It is a powerful illustration of the disciplined, methodical way IFS approaches complex programmes. 

“Do a match fit phase, and that will de-risk the future programme.” 

He paired it with two other principles he considers essential. The first is clear governance and sponsorship. The second he called working “two in the box,” where the business and IT operate in lockstep towards one shared set of objectives, as a single enterprise team. 

For organizations preparing for Industrial AI, that combination of preparation, sponsorship, and business alignment is what turns an ambitious programme into a delivered one. It is also a good example of the depth of experience IFS brings to every customer engagement. 

Where can Industrial AI make the biggest difference in energy operations? 

Industrial AI makes the biggest difference by transforming end-to-end processes and removing the manual effort that slows them down. Robi described how much value is unlocked when organizations move beyond stitching data together by hand and let AI do that work intelligently, in real time. 

This is where he sees the clearest opportunity. Organizations can apply AI directly to the bottlenecks inside their existing processes, building agents on top of their data and alongside their current systems. It allows them to modernize quickly and leapfrog traditional ways of working, all while protecting the systems they rely on every day. 

“We can transform and leapfrog many of the traditional ways of doing things.” 

Coming from Robi’s background in energy and resources, where the margin for error is zero, this resonated with me. He is describing a way to modernize that fully respects the reliability and safety those industries demand, while still moving at pace. That balance of rigour and speed is exactly what IFS delivers for energy and utilities customers. 

What excites a CIO most about where IFS is heading? 

I closed by asking Robi what excites him most about the journey IFS is on. His answer was about how real and how tangible it all is. 

He talked about the full stack of how IFS applies AI: the embedded AI inside the products, the platform-level AI that connects multiple data sets, and the work going directly to customers to solve specific, high-value problems. Seeing that combination come together is what convinced him that IFS is genuinely ahead. 

“It’s what we’re doing day in and day out.” 

That conviction is what made this episode matter to me. Robi has spent his entire career inside the industries IFS serves, and he chose to join because he saw IFS delivering on Industrial AI in a way he described as very real and very tangible. Hearing a CIO of his calibre speak with that level of confidence told me a great deal about the strength of where IFS stands today. 

What I took away from this conversation is a confident, encouraging message for any leader thinking about Industrial AI. The value is available now. With good preparation and an experienced partner, organizations can start where their data is strongest, prove real results early, and grow from there. That is precisely the journey IFS is helping customers make every day.